Alpha Standard
Defines the six pillars, 48 requirements, evidence rules, controls, score anchors, and governance gates.
The Alpha Standard Version 1 · Six pillars
Alpha assesses the enterprise governance system around material AI and agentic deployments, not an individual model in isolation. Six weighted pillars define governance quality. A separate four-quadrant matrix helps boards govern both risk and opportunity.
One integrated system
This separation prevents materiality, market opportunity, and public visibility from being mistaken for governance quality.
Alpha Standard
Defines the six pillars, 48 requirements, evidence rules, controls, score anchors, and governance gates.
Alpha AIGR
Expresses governance quality as one versioned rating opinion, with a public-information or verified-assessment evidence basis.
Alpha GMI and matrix
Alpha GMI expresses governance materiality. The matrix routes internal and external risks and opportunities. Neither directly raises the Alpha AIGR.
Six pillars
These are the only canonical human-facing pillar names in Version 1. Stable technical IDs preserve the underlying data lineage.
P1 · 20%
Who is responsible for AI, and can the board hold them accountable? Board authority, executive ownership, decision rights, governance structure, accountability, and reliable reporting.
Evidence considered
P2 · 22%
Can AI operate safely and withstand attack, failure, and disruption? Safety engineering, cybersecurity, resilience, incident readiness, and controls for material AI and agentic systems.
Evidence considered
P3 · 15%
Is data protected, and are AI uses, decisions, and claims clear? Data governance, privacy, provenance, inventory, disclosure, explainability, and traceable claims about AI use.
Evidence considered
P4 · 14%
Are people treated fairly, protected from harm, and able to challenge decisions? Fairness, human rights, workforce and customer impacts, accessibility, notice, challenge, and remediation.
Evidence considered
P5 · 15%
Are legal duties, vendors, models, and external dependencies governed? Legal and regulatory applicability, third-party oversight, contract controls, supply-chain governance, and stakeholder duties.
Evidence considered
P6 · 14%
Can the enterprise detect problems, intervene, correct them, and learn? Continuous monitoring, independent assurance, override and shutdown capability, corrective action, and learning from outcomes.
Evidence considered
Four-quadrant view
Each material signal, finding, incident, opportunity, or governance action is classified once by scope and posture, then linked to one or more pillars.
Internal Opportunity
What internal AI capability can improve how the enterprise operates?
External Opportunity
What market, customer, investment, or partnership opportunity can AI create?
Internal Risk
What internal AI exposure must be governed, controlled, or escalated?
External Risk
What external threat, dependency, regulatory change, or competitive event requires a response?
Rating rule
The matrix is a classification and accountability layer, not a seventh pillar. It has no weight and never changes the Alpha AIGR directly. Alpha evaluates how well an enterprise governs an opportunity, not how large or profitable that opportunity may be.
Boundaries
Alpha rates
Alpha does not rate